---
base_model: NlpHUST/ner-vietnamese-electra-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_ner-token_classification_v1.0
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# my_awesome_ner-token_classification_v1.0

This model is a fine-tuned version of [NlpHUST/ner-vietnamese-electra-base](https://huggingface.co/NlpHUST/ner-vietnamese-electra-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7184
- Precision: 0.5603
- Recall: 0.6333
- F1: 0.5946
- Accuracy: 0.8261

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.478         | 1.9991  | 2313  | 0.5109          | 0.5864    | 0.5956 | 0.5910 | 0.8411   |
| 0.3927        | 3.9983  | 4626  | 0.5095          | 0.5834    | 0.6186 | 0.6005 | 0.8401   |
| 0.3111        | 5.9974  | 6939  | 0.5813          | 0.5434    | 0.6335 | 0.5850 | 0.8258   |
| 0.2339        | 7.9965  | 9252  | 0.6137          | 0.5515    | 0.6312 | 0.5887 | 0.8261   |
| 0.1983        | 9.9957  | 11565 | 0.6743          | 0.5719    | 0.6243 | 0.5969 | 0.8305   |
| 0.1565        | 11.9948 | 13878 | 0.7044          | 0.5594    | 0.6372 | 0.5958 | 0.8250   |
| 0.1657        | 13.9939 | 16191 | 0.7184          | 0.5603    | 0.6333 | 0.5946 | 0.8261   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1